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Concentrations of selected volatile organiccompounds at kerbside
and background sites incentral LondonValach, A. C.; Langford, B.;
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DOI:10.1016/j.atmosenv.2014.06.052
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sites in central London', Atmospheric Environment, vol. 95,
pp.456-467. https://doi.org/10.1016/j.atmosenv.2014.06.052
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Accepted Manuscript
Concentrations of selected volatile organic compounds at
kerbside and backgroundsites in central London
A.C. Valach, B. Langford, E. Nemitz, A.R. MacKenzie, C.N.
Hewitt
PII: S1352-2310(14)00498-1
DOI: 10.1016/j.atmosenv.2014.06.052
Reference: AEA 13076
To appear in: Atmospheric Environment
Received Date: 25 January 2014
Revised Date: 9 June 2014
Accepted Date: 25 June 2014
Please cite this article as: Valach, A.C., Langford, B., Nemitz,
E., MacKenzie, A.R., Hewitt, C.N.,Concentrations of selected
volatile organic compounds at kerbside and background sites in
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http://dx.doi.org/10.1016/j.atmosenv.2014.06.052
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Concentrations of selected volatile organic compounds at 1
kerbside and background sites in central London 2
3
A. C. Valacha, B. Langfordb, E. Nemitzb, A. R. MacKenziec and C.
N. Hewitta 4
[a]{Lancaster Environment Centre, Lancaster University,
Lancaster, LA1 4YQ, United Kingdom 5
([email protected]; [email protected])} 6
[b]{Centre for Ecology & Hydrology, Bush Estate, Penicuik,
Midlothian, EH26 0QB, United Kingdom 7
([email protected]; [email protected])} 8
[c]{School of Geography, Earth and Environmental Sciences,
University of Birmingham, Edgbaston, 9
Birmingham, B15 2TT, United Kingdom ([email protected])}
10
Correspondence to: A.C. Valach ([email protected], +44
7547179256) 11
12
Keywords: Volatile organic compound; Mixing ratio ; Proton
transfer reaction-mass spectrometer; 13
Automatic hydrocarbon network ; ClearfLo ; London. 14
Abstract 15
Ground-level concentrations of nine volatile organic compounds
(VOCs) were measured using a 16
proton transfer reaction-mass spectrometer (PTR-MS) in central
London at an urban background 17
(North Kensington, NK, during 16th
- 25th
Jan 2012) and a kerbside site (Marylebone Rd, MRd, during 18
25th
Jan - 7th
Feb 2012) as part of the winter intensive observation period of
the ClearfLo project. Site 19
comparisons indicated that VOC concentrations at the urban
background site were significantly 20
lower than at the kerbside site (ratio MRd/NK of 2.3). At the
kerbside site PTR-MS measurements of 21
aromatics (benzene, toluene, C2- and C3-benzenes) were compared
with the gas chromatography – 22
flame ionization detector data from the UK Government’s
Automatic Hydrocarbon Network. Very 23
good qualitative agreement was observed between the two methods
(r = 0.90 - 0.91, p
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2 Methods 62
2.1 Measurement sites and meteorology 63
Details of both the North Kensington (NK) background and
Marylebone Rd (MRd) kerbside sites are 64
compared (Supplementary content Table A1). Air was pumped
through a PTFE inlet (and PTFE filter 65
at MRd) attached to 1/4” OD PTFE tubing to a high sensitivity
proton transfer reaction-mass 66
spectrometer (PTR-MS; Ionicon Analytik GmbH, Innsbruck,
Austria). 67
Meteorological measurements were co-located with the inlet at NK
(Figure 1 and Supplementary 68
content Table A1). The mean UK temperature in January was 6.0
°C, i.e. 1.3 °C above the 1971-2000 69
average (UK Met Office, 2012), although February experienced low
temperatures and snowfall, 70
which is uncommon in London. 71
2.2 VOC sampling 72
VOC mixing ratios were measured on-line using a PTR-MS ( de Gouw
and Warneke, 2007; Lindinger 73
et al., 1998). The instrument was operated in multiple ion
detection (MID) and mass scan (SCAN) 74
modes (Supplementary content A1). In MID mode the quadrupole
mass spectrometer scanned 75
through 11 pre-determined masses, to which the following
compounds were ascribed: m/z 21 76
(indirect quantification of m/z 19 primary ion count [H3O+] via
isotopologue [H3
18O
+]), m/z 33 77
(methanol), m/z 39 (indirectly quantified m/z 37 first cluster
[H3O+
.H2O+]), m/z 42 (acetonitrile), m/z 78
45 (acetaldehyde) m/z 59 (acetone/propanal), m/z 69
(cycloalkanes/isoprene), m/z 79 (benzene), 79
m/z 93 (toluene), m/z 107 (C2-benzenes) and m/z 121
(C3-benzenes). 80
The UK national Automatic Hydrocarbon Network (AHN) station at
MRd measures 29 different 81
hydrocarbons using a gas chromatography-flame ionization
detector (GC-FID, AutoSystem XL; 82
PerkinElmer Inc., USA). This method complies with standards set
out by the European Air Quality 83
Directive (Broadway and Tipler, 2008). A 40 min continuous
sampling period provides hourly means 84
(Supplementary content A2). 85
PTR-MS measures in unit mass resolution and a fragment may
derive from several parent 86
compounds, therefore each detected mass may relate to one or
more compounds. Where possible, 87
measurements should be verified by more specific analytical
techniques, such as GC-FID. 88
Unfortunately, only benzene, toluene, some C2- and C3-benzenes
were verified by the AHN. 89
2.3 Quality analyses and data handling 90
The PTR-MS was calibrated over a range of concentrations using a
certified multi-component VOC 91
gas standard (Ionimed Analytik GmbH, Austria). The measured
instrument sensitivities were then 92
used to convert normalized count rates of RH+ to volume mixing
ratios (Langford et al., 2010a). The 93
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instrument background was quantified using a platinum catalyst
and subtracted from the ambient 94
measurements. Since the background was determined for dry air,
corrections for humidity effects on 95
some compounds had to be applied and were associated with large
uncertainties (Supplementary 96
content B). 97
A low pass filter was applied to smooth the data and reduce
instrumental noise. Spearman’s rank 98
correlation coefficients and Wilcoxon rank sum tests were used
in statistical analyses due to the data 99
distributions. 100
3 Results & Discussion 101
3.1 VOC concentrations 102
VOC concentrations measured by the PTR-MS at the North
Kensington (NK) background site (Figure 103
2a) and at the Marylebone Rd (MRd) kerbside site (Figure 2b) are
summarized in Table 1a and 1b. At 104
both sites methanol, acetaldehyde and acetone, all oxygenated
compounds, were the most 105
abundant. Methanol has a variety of biogenic, anthropogenic and
atmospheric sources (Cady-Pereira 106
et al., 2012). Acetone has some biogenic contributions but
solvents and tailpipe emissions were 107
most likely the main sources (de Gouw et al., 2005; Reissell et
al., 1999; Warneke et al., 1999). Both 108
have a low photochemical reactivity with OH resulting in longer
atmospheric lifetimes, which also 109
contributed to the relatively high mixing ratios. The compounds
with the lowest mixing ratios at both 110
sites were acetonitrile and cycloalkanes/isoprene. Although
these are emitted from vehicle exhaust, 111
their volume mixing ratios were much lower than other
traffic-related compounds. The isoprene 112
component of m/z 69 was estimated at 22% and presumably from
traffic as the biogenic component 113
was absent due to the season (Borbon et al., 2001). Comparison
with GC-FID isoprene 114
concentrations at NK inferred that cycloalkanes provided a
significant contribution to m/z 69 115
(Supplementary content C) (Erickson et al., 2014 ;Yuan et al,
2014). Although globally biomass 116
burning is the main source of acetonitrile (Holzinger et al.,
2001), in urban areas emissions from 117
vehicle exhaust are prominent as diurnal profiles resembled a
double rush hour pattern (Section 3.4) 118
with some increased acetonitrile emissions occurring at low
temperatures possibly from solid fuel 119
burning (Section 3.3). 120
Mixing ratios for most of the compounds agreed with or were
lower than observations from other 121
urban areas, but benzene and C2-benzenes concentrations were
slightly higher at MRd compared 122
with previous observations in UK cities (Langford et al., 2009,
2010b). The measurement proximity to 123
the source emissions must be considered; for example, Langford
et al. (2010b) reported 124
concentration measurements from tall towers where the effects of
dilution and photochemical loss 125
are greater. 126
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During both measurement periods the beginnings and ends were
marked by high pollution episodes 127
(16th
-18th
, 24th
-28th
Jan and 3rd
-7th
Feb). 128
3.1.1 Site comparison 129
The volume mixing ratios of all compounds were significantly
different (p
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Humidity dependencies on instrument sensitivities and background
were thoroughly investigated in 160
the laboratory after the campaign. Calibrations showed no
significant variations of sensitivity with 161
humidity. Corrections were applied to compounds showing humidity
effects on instrument 162
background, but not all effects could be recreated and accounted
for, such as humidity effects on 163
inlet impurities affecting aromatics (Supplementary content B).
164
Fragmentation can become a concern at higher E/N ratios (de Gouw
and Warneke, 2007; Maleknia 165
et al., 2007; Warneke et al., 2003). An E/N ratio of 125 Td was
used in this study as this represents a 166
compromise between reagent ion clustering and fragmentation
suppression (Hewitt et al., 2003). 167
Some fragmentation can still occur, as several studies using a
coupled GC-PTR-MS with a range of 168
E/N ratios have identified various fragment ions. Benzaldehyde,
ethyl benzene and xylene isomers 169
with m/z 107 may produce fragments of about 30-40% at m/z 79
with higher E/N ratios (Maleknia et 170
al., 2007), as well as propyl benzene isomers and smaller
contributions of fragments of butyl 171
benzene (Warneke et al., 2003). As only o-xylene was present in
the calibration standard, fragments 172
from other compounds at that mass cannot be accounted for and
are likely to have contributed to 173
the increased PTR-MS signal. It is estimated that with an
electrical field strength of 125 Td around 174
15% C2-benzenes may have contributed to m/z 79. Interference
from fragments at m/z 93 could 175
include a range of biogenic terpenes and their isomers (Maleknia
et al., 2007). 176
Previous studies have shown that there is good correlation
between PTR-MS and GC-FID, however 177
the quantitative agreement can be poor with differences of up to
a factor of 2 (de Gouw and 178
Warneke, 2007; Kato et al., 2004). The value for m/z 121 is
somewhat higher than cited in the 179
literature, which may be due to humidity effects on inlet
impurities which could not be accounted 180
for after the campaign, as well as isobaric interference from
compounds and fragments not 181
measured by the AHN. All four m/z showed very good correlations
(Figure 4) with r 0.90-0.91 182
(p
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3.3 VOC correlations and ratios 192
Correlations between the different VOCs yielded coefficients (r)
ranging between -0.23 and 0.97 at 193
NK and -0.20 to 0.87 at MRd (p
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This model simulates the origin of the air masses affecting the
ClearfLo sites within the previous 24h 225
(Bohnenstengel et al., in review). Shifts between high and low
pollution episodes often are 226
correlated with changes in wind direction and intensity. For the
low pollution periods (19th
-23rd
Jan 227
and 31st
Jan-2nd
Feb) strong westerlies brought air masses with regional
influences and high b/t 228
ratios of 0.91 (0.64-1.31). The high pollution episodes
(24th
-25th
Jan and 4th
Feb) showed low wind 229
speeds resulting in shorter travel distances of the air masses
and stronger local London influences 230
(up to 87%, campaign average 37%) and corresponding low b/t
ratios of 0.48 (0.39-0.58). 231
3.4 Diurnal averages 232
Meteorological conditions can mask emission patterns, therefore
diurnal averages are used to aid in 233
their identification (Figure 7). Concentrations can depend on
the mixing height in the boundary 234
layer, however LIDAR measurements showed little diurnal
variation in the seasonally shallow mixing 235
height (500-1000m) (Bohnenstengel et al., in review). All
compounds, bar methanol, showed a 236
double rush hour peak during weekdays (07:00-10:00 and
17:00-20:00 GMT) and lower 237
concentrations with less variability on weekends (Figure 7, E -
H), suggesting vehicle exhaust as a 238
major source. At MRd, rush hour peaks were less pronounced due
to the continuously high daytime 239
traffic density (68002 vehicles per day; Department for
Transport, 2012), which causes the road to 240
saturate for prolonged periods during the day. 241
The early morning minima (04:00 – 06:00 GMT) can be attributed
to reduced human activity which 242
sharply increases during the morning rush hour peak (07:00-10:00
GMT) (Figure 7, F – H). Methanol 243
and acetone have numerous sources and longer atmospheric
lifetimes resulting in no clear diurnal 244
pattern (Figure 7, A and B). 245
3.5 Analyses of wind direction dependence 246
3.5.1 Synoptic polar plots 247
Using wind speed and direction measurements from the BT tower
(190 m a.g.l.), polar plots were 248
constructed for compound mixing ratios (Figure 8) using a
generalized additive model (GAM) (Hastie 249
and Tibshirani, 1990; Wood, 2006) to interpolate between
averaged data points in the R package 250
openair (Carslaw, 2012; Carslaw and Ropkins, 2012). At NK high
concentrations for most compounds 251
were associated with low wind speeds (i.e. 5 m s-1
possibly representing 253
pollution transported to the site from a biodiesel production
facility located 1km SW of the site. 254
Biodiesel production from waste cooking oil by
transesterification often involves evaporating 255
methanol. 256
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At MRd methanol showed high concentrations with S and N winds
>10 m s-1
, whereas benzene is 257
representative of the other compounds with patches of increased
concentrations at speeds of 5-10 258
m s-1
. The WSW and ENE patches coincide with the directional layout
of Marylebone Rd, while the 259
SSW source may originate from traffic in the Marble Arch/Hyde
Park Corner area, which boasted the 260
highest annual mean traffic count of 100574 motor vehicles per
day in all of Westminster, London 261
(DfT, 2012). 262
3.5.2 Synoptic wind direction dependencies and comparison with
NAEI 263
To quantify wind direction dependencies (Section 3.5.1) and
compare measured VOC mixing ratios at 264
MRd with the National Atmospheric Emissions Inventory (NAEI) for
estimated emissions, general 265
linear models were used for each compound concentration against
the four wind direction 266
categories. There was no significant difference in wind speed
with direction. Correlations of VOC 267
concentrations with wind speed showed weak negative
relationships (r = -0.38 to -0.14, p < 0.05) 268
indicating that a dilution effect depending on wind speed from
above-canyon air mass mixing may 269
play a small role in street canyon concentrations. 270
All species showed significant differences in mixing ratios with
wind direction (F- statistic 6.73 - 41.8, 271
p
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significantly lower mixing ratios than at the MRd kerbside site,
even though AHN data showed that 290
kerbside concentrations were higher during the first measurement
period, suggesting site 291
differences due to the location with different source strengths
and proximity. 292
Comparison of PTR-MS and GC-FID data from MRd for aromatics
showed good correlation and 293
qualitative agreement. However, PTR-MS data were significantly
higher possibly due to some 294
isobaric interference from additional compounds and fragments,
and possibly systematic errors 295
introduced during instrument background corrections. Short term
variations in the ratio of traffic 296
related compounds from differences in traffic density, driving
style, vehicle and fuel types were 297
observed by PTR-MS at MRd site and higher correlations with CO
for PTR-MS than the GC-FID 298
measurements were likely due to the fast response and longer
sampling times of the PTR-MS. The 299
AHN can only report hourly arithmetic means due to the methods
employed, possibly leading to a 300
reporting bias and a loss of information on short term
variability. 301
Elevated concentrations were mostly observed when synoptic-scale
wind speeds were low at NK as 302
dispersion of localised emissions was reduced. However, some
non-local emission sources were 303
detected using polar plots and possible sources were identified.
There were significant differences in 304
VOC concentrations with wind direction. When compared with
estimated benzene emissions by the 305
NAEI, estimates were less representative when VOC concentrations
were high, as they are unable to 306
capture the influence of city background emissions and reduced
local sub-grid emission source 307
contributions. 308
Acknowledgements 309
We thank the UK Natural Environment Research Council (NERC)
ClearfLo consortium (grant number 310
NE/H00324X/1) for collaboration. ClearfLo was coordinated by the
National Centre for Atmospheric 311
Science (NCAS). Amy Valach thanks NERC for a PhD studentship.
Thanks to the Sion Manning School 312
and David Green (King’s College London) for site access, Zoë
Fleming (NCAS and University of 313
Leicester) for the NAME dispersion plots, the UK Met Office for
use of the NAME model, Janet 314
Barlow (University of Reading) for the meteorological and CO
measurements on the BT tower, James 315
Hopkins and Rachel Holmes (University of York) for the GC-FID
isoprene data, and James Lee (NCAS 316
and University of York) for the meteorological and CO data at
NK. 317
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Berkowitz, C. M. & Molina, L. T. (2010). Comparison of
aromatic hydrocarbon measurements made 377
by PTR-MS, DOAS and GC-FID during the MCMA 2003 Field
Experiment. Atmospheric Chemistry and 378
Physics, 10(4), 1989–2005, doi:10.5194/acp-10-1989-2010. 379
Jones, A.R., Thomson, D.J., Hort, M. & Devenish, B. (2007).
The U.K. Met Office's next-generation 380
atmospheric dispersion model, NAME III. In B. C. A.-L., Air
Pollution Modeling and its Application 381
XVII: Proceedings of the 27th NATO/CCMS International Technical
Meeting on Air Pollution 382
Modelling and its Application (pp. 580-589). Springer. 383
Kansal, A. (2009). Sources and reactivity of NMHCs and VOCs in
the atmosphere: a review. Journal of 384
Hazardous Materials, 166(1), 17–26.
doi:10.1016/j.jhazmat.2008.11.048 385
Kato, S., Miyakawa, Y., Kaneko, T. & Kajii, Y. (2004). Urban
air measurements using PTR-MS in Tokyo 386
area and comparison with GC-FID measurements, International
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(2), 103-110, doi:10.1016/j.ijms.2004.03.013 388
Kim, Y. M., Harrad, S., & Harrison, R. M. (2001).
Concentrations and sources of VOCs in urban 389
domestic and public microenvironments. Environmental Science
& Technology, 35(6), 997–1004. 390
Kuster, W. C., Jobson, B. T., Karl, T., Riemer, D., Apel, E.,
& Goldan, P. D. (2004). Intercomparison of 391
Volatile Organic Carbon Measurement Techniques and Data at La
Porte during the TexAQS2000 Air 392
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221–228. 393
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Langford, B., Davison, B., Nemitz, E., & Hewitt, C. N.
(2009). Mixing ratios and eddy covariance flux 394
measurements of volatile organic compounds from an urban canopy
(Manchester, UK). Atmospheric 395
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volatile organic compounds from a South-398
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D., Davison, B., Hopkins, J. R., Lewis, A. C. 401
& Hewitt, C. N. (2010b). Fluxes and concentrations of
volatile organic compounds above central 402
London, UK. Atmospheric Chemistry and Physics, 10, 627–645.
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Lindinger, W., Hansel, A., & Jordan, A. (1998). On-line
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doi:10.1016/0015-1882(95)90197-3. 406
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Yuan, B., Warneke, C., Shao, M. & de Gouw, J. (2014).
Interpretation of volatile organic compound 432
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435
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Figure 1. Top: 5 min means of ambient air temperature (°C) and
relative humidity (%) during the 436
campaign 16th
Jan – 7th
Feb 2012. Bottom: Frequency plots of mesoscale wind direction
(%) with 437
subcategories of wind speed (m s-1
) using 30 min mean data from the WXT520 (Vaisala Ltd) at 190m
438
on the BT tower at NK (16th
– 25th
Jan 2012) (left) and MRd (25th
Jan – 7th
Feb 2012) (right). 439
Figure 2. 5min mean (grey) and 25 min means (black) with
detection limits (dashed line) for all 440
measured VOCs (ppb) at (a) North Kensington and (b) Marylebone
Rd (16th
Jan – 7th
Feb 2012). M/z 441
are 33 (methanol), 42 (acetonitrile), 45 (acetaldehyde), 59
(acetone), 69 (cycloalkanes/isoprene), 79 442
(benzene), 93 (toluene), 107 (C2-benzenes) and 121
(C3-benzenes). 443
Figure 3. 1h means for benzene, toluene, C2- and C3-benzenes
mixing ratios (ppb) measured by the 444
PTR-MS (solid line) and GC-FID (dashed line) at Marylebone Road
(25th
Jan – 7th
Feb 2012). 445
Figure 4. Scatter plots of 1h mean VOC concentrations (ppb)
(benzene, toluene, C2- and C3-benzenes) 446
of PTR-MS against GC-FID measurements at Marylebone Road
(25th
Jan – 7th
Feb 2012) with reduced 447
major axis (RMA) linear regressions, ± 99th
confidence intervals, 1:1 line (dotted) with r-values. 448
Figure 5. Scatter plots of representative VOC correlations
measured at North Kensington (left) and 449
Marylebone Rd (right) (16th
Jan – 7th
Feb 2012) using 5 min means (ppbv) with ambient air 450
temperature (°C) at time of sampling (colour bar). 451
Figure 6. 24 hour back trajectories from the Met Office NAME
dispersion model at North Kensington 452
(16th
Jan-7th
Feb 2012). Daily release for 3 hours from midday (20 m height)
tracking the surface 453
layer only (0-100m) for the 24 hours prior. Reproduced with
permission from Zoë Fleming (NCAS, 454
University of Leicester). 455
Figure 7. Diurnal plots of 25min averages (ppb) for
representative VOCs at North Kensington and 456
Marylebone Road (16th
Jan – 7th
Feb 2012) with the 95% confidence interval (shaded areas), all
days 457
(solid line), weekdays (dashed line) and weekends (dotted line).
458
Figure 8. Representative selection of polar plots of synoptic
wind speed (m s-1
) against wind 459
direction (°) from the BT tower (190m) with VOC mixing ratios
(ppb) as a third variable (colour bar) 460
for methanol (m/z 33), acetonitrile (m/z 42) and benzene (m/z
79) at North Kensington (16th
-25th
Jan 461
2012) (top) and Marylebone Rd (25th
Jan – 7th
Feb 2012) (bottom). 462
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463
Table 1a. Summary of 5 min averages of VOC mixing ratios (ppb)
at North Kensington, London (16th - 25th Jan 2012). 464
Mixing
ratios
Methanol Aceto-
nitrile
Acetal-
dehyde
Acetone Cycloalkanes/
Isoprene
Benzene Toluene* C2-
benzenes
C3-
benzenes
(ppb) m/z 33 m/z 42 m/z 45 m/z 59 m/z 69 m/z 79 m/z 93 m/z 107
m/z 121
Lifetime
(OHa)
12 d 1.5 yr 8.8 h 53 d 1.4 h 9.4 d 1.9 d 5.9 hb
4.3 hc
N 2219 2202 2211 2213 2199 2227 2226 2225 2226
LoD 0.37 0.04 0.18 0.06 0.005 0.04 0.01 0.08 0.03
Min. 2.86
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Table 1b. Summary of 5min averages of VOC mixing ratios (ppb) at
Marylebone Rd, London (25th
Jan - 7th
Feb 2012). 470
471
472
Mixing
ratios
Methanol Aceto-
nitrile
Acetal-
dehyde
Acetone Cycloalkanes/
Isoprene
Benzene Toluene C2-
benzenes
C3-
benzenes
(ppb) m/z 33 m/z 42 m/z 45 m/z 59 m/z 69 m/z 79 m/z 93 m/z 107
m/z 121
N 2712 2718 2716 2705 2720 2715 2713 2708 2715
LoD 0.37 0.04 0.18 0.06 0.005 0.04 0.01 0.08 0.03
Min. 1.34 0.08 0.38 0.70 0.15 0.06 0.02
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Table 2 Summary of 1h averages of compounds (ppb) measured by
both PTR-MS and GC-FID at Marylebone Rd, London 473 (25
th Jan – 7
th Feb 2012). 474
PTR-MS GC-FID
Mixing ratios Benzene Toluene C2-
benzenes
C3-
benzenes
Benzene Toluene C2-
benzenes
C3-
benzenes
(ppb) m/z 79 m/z 93 m/z 107 m/z 121 m/z 79 m/z 93 m/z 107 m/z
121
N 274 274 274 256 302 302 302 302
LoD 0.04 0.01 0.08 0.03 0.01 0.01 0.01 0.01
Min. 0.17 0.13 0.29 0.13 0.14 0.07 0.03 0.01
1st quartile 0.39 0.52 0.87 0.46 0.30 0.38 0.57 0.13
Median 0.57 0.82 1.23 0.91 0.42 0.61 0.83 0.24
Geom. mean 0.58 0.95 1.30 0.81 0.41 0.66 0.86 0.24
Arithm. mean 0.63 1.17 1.44 1.07 0.47 0.87 1.01 0.33
3rd quartile 0.82 1.53 1.89 1.51 0.58 1.09 1.32 0.46
Max. 2.26 6.42 5.12 3.71 1.42 5.17 4.51 1.45
SD 0.32 1.01 0.81 0.74 0.23 0.83 0.63 0.29
Skew 1.30 2.06 1.38 0.93 1.53 2.33 1.39 1.27
Kurtosis 2.65 5.21 2.53 0.39 2.98 6.36 2.13 1.16
475
476
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Table 3. Mean VOC/CO ratios for volume mixing ratios (ppbv/ppbv)
at NK and MRd, London (16th
Jan - 7th
Feb 2012). 477
Compound ClearfLo
NKa MRd
PTR-MS PTR-MSb GC-FID
c
[VOC]/[CO] r [VOC]/[CO] r [VOC]/[CO] r
Methanol 2.13E-02 0.28 1.20E-02 0.27
Acetonitrile 2.70E-04 0.87 5.21E-04 0.55
Acetaldehyde 2.14E-03 0.93 4.14E-03 0.84
Acetone 4.53E-03 0.62 3.18E-03 0.74
Cycloalkanes/
Isoprene 5.74E-04 0.80 1.13E-03 0.82
Benzene 1.08E-03 0.96 1.59E-03 0.75 1.58E-03 0.68
Toluene 2.07E-03 0.93 3.09E-03 0.72 3.33E-03 0.65
C2-benzenes 2.16E-03 0.89 3.69E-03 0.66 4.70E-03 0.58
C3-benzenes 1.72E-03 0.86 2.60E-03 0.65 1.61E-03 0.68 aN =
226,
bN =256-274,
cN =302 478
479
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−5
05
10
Tem
pera
ture
(°C
)
Jan 16 Jan 21 Jan 26 Jan 31 Feb 05
4060
80
Date (2012)
Rel
ativ
e hu
mid
ity (
%)
Date (2012)
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North Kensington wind frequency
Frequency of counts by wind direction (%)
10%
20%
30%
40%
50%
60%
70%
wind spd.
0.12−0.2
0.2−0.4
0.4−0.6
0.6−0.8
0.8−1
1−1.2
1.2−1.4
1.4−1.6
1.6−1.8
1.8−2.8
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Marylebone Rd wind frequency
Frequency of counts by wind direction (%)
10%
20%
30%
40%
50%
60%
70%
wind spd.2
0.3−2
2−4
4−6
6−8
8−10
10−12
12−15
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to−
nitr
ile[p
pb]
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